Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …

We are living in a world where massive end devices perform computing everywhere and
everyday. However, these devices are constrained by the battery and computational …

Driven by the visions of Internet of Things and 5G communications, the edge computing
systems integrate computing, storage, and network resources at the edge of the network to …

With the rapid development of mobile internet and Internet of Things applications, the
conventional centralized cloud computing is encountering severe challenges, such as high …

Currently, we are experiencing a technological shift, which is expected to change the way
we program and interact with the world. Cloud computing and mobile computing are two …

With the advent of Internet of Things (IoT) connecting billions of mobile and stationary
devices to serve real-time applications, cloud computing paradigms face some significant …

Mobile edge computing (MEC) provides a promising approach to significantly reduce
network operational cost and improve quality of service (QoS) of mobile users by pushing …

The performance of mobile computing would be significantly improved by leveraging cloud
computing and migrating mobile workloads for remote execution at the cloud. In this paper …

Glimpse is a continuous, real-time object recognition system for camera-equipped mobile
devices. Glimpse captures full-motion video, locates objects of interest, recognizes and …

Mobile applications are becoming increasingly computation-intensive, while the computing
capability of portable mobile devices is limited. A powerful way to reduce the completion …